Recent developments on multiscale simulations for rheology and complex flow of polymers

Abstract This review summarized the multiscale simulation (MSS) methods for polymeric liquids. Since polymeric liquids have multiscale characteristics of monomeric, mesoscopic, and macroscopic flow scales, MSSs that relate different hierarchical levels are adequate to reproduce flow properties accurately. Our review includes pioneering studies to the most advanced MSS studies on rheology predictions and flow simulations of polymeric liquids. We discuss two major types of MSS methods: the bottom-up and model-embedded MSS methods. The former method mainly connects all-atom molecular dynamics models and mesoscopic models to predict rheological properties. In contrast, the latter method, where a microscopic or mesoscopic model is embedded in a macroscopic computational domain, is designed to predict macroscopic flow properties. Finally, we also discuss MSS methods using machine learning techniques. Graphical abstract

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Publication Details

Journal
Korea-Australia Rheology Journal
Published
2024-10-24
DOI
https://doi.org/10.1007/s13367-024-00112-2
Citations
2
Primary Topic
Rheology and Fluid Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.44

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article

Recent developments on multiscale simulations for rheology and complex flow of polymers

Takeshi Sato, Kenji Yoshimoto
2 citations
Korea-Australia Rheology Journal
Rheology and Fluid Dynamics Studies
0.44
article

Recent developments on multiscale simulations for rheology and complex flow of polymers

Takeshi Sato, Kenji Yoshimoto
article en
2 citations

Abstract

Abstract This review summarized the multiscale simulation (MSS) methods for polymeric liquids. Since polymeric liquids have multiscale characteristics of monomeric, mesoscopic, and macroscopic flow scales, MSSs that relate different hierarchical levels are adequate to reproduce flow properties accurately. Our review includes pioneering studies to the most advanced MSS studies on rheology predictions and flow simulations of polymeric liquids. We discuss two major types of MSS methods: the bottom-up and model-embedded MSS methods. The former method mainly connects all-atom molecular dynamics models and mesoscopic models to predict rheological properties. In contrast, the latter method, where a microscopic or mesoscopic model is embedded in a macroscopic computational domain, is designed to predict macroscopic flow properties. Finally, we also discuss MSS methods using machine learning techniques. Graphical abstract

Korea-Australia Rheology JournalVol. 36(4)
Kanazawa University (JP), Kanazawa Institute of Technology (JP)
Kanazawa University, RIKEN, Precursory Research for Embryonic Science and Technology
Openalex Percentile: Top 44%
Rheology and Fluid Dynamics Studies
0.44
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